In DE 100 64 182 and DE 103 24 692, the entire content of which is incorporated into the present application by reference, control and automation concepts for harbour mobile cranes are disclosed. In these rotary boom cranes the manipulator 416 for grabbing the load is suspended on ropes 410 and positioning of the manipulator for grabbing containers causes spherical swaying movements. The control concepts use trajectory tracking control to control the movement of the load and to automatically avoid sway, thereby increasing the effectiveness of the cargo handling process.
For such control systems a method for controlling the orientation of the crane load is known from DE 100 29 579, the entire content of which is incorporated into the present application by a reference. There, the hook suspended on ropes has a rotator unit containing a hydraulic drive 412, such that the manipulator 416 for grabbing containers can be rotated around a vertical axis. Thereby it is possible to vary the orientation of the crane loads. If the crane operator or the automatic control gives a signal to rotate the manipulator and thereby the load around the vertical axis, the hydraulic motors of the rotator unit are activated and a resulting flow rate causes a torque. As the hook is suspended on ropes, the torque would result in a torsional oscillation of the manipulator and the load. To position the load at a specific angle φL, this torsional oscillation has to be compensated.
The known control method uses a dynamic model of the system based on the equations of motion of a physical model of the crane, the known anti-torsional oscillation control 212 consisting of a trajectory planning module 310 and a trajectory tracking module. The trajectory planning module calculates the trajectory of the variables describing the state of the system and produces a reference function. The trajectory tracking control can be divided into disturbance rejection, feed forward control and the state feed back control. The parameters used by the control unit are the mass of the load and most importantly, the moment of inertia of the load.
However, the distribution of mass inside the load, e.g. a container, is unknown and therefore the moment of inertia of the load is not known, either. The moment of inertia JL of the load therefore has to be estimated. In the known control system, this is done by assuming a homogenous mass distribution inside the load and calculating an estimated moment of inertia JL of the load from the mass of the container 418 and the known dimensions of the container only.
However, the distribution of load inside a container is usually far from homogenous, such that the estimated value of the load JL is only a very imprecise approximation. As the control unit uses the moment of inertia JL of the load as a parameter for controlling the orientation of the crane load, the difference between the true value of the moment of inertia JL and the rough estimate leads to an imprecision in the control of the orientation of the load.
The aim of the present disclosure is therefore to provide a method for controlling the orientation of the crane load that has better precision.
This aim is achieved by a method for controlling the orientation of a crane load, wherein the control unit for controlling the rotational angle φL of the load is an adaptive control unit wherein the moment of inertia JL of the load is identified during operation of the crane based on data obtained by measuring the state of the system.
Thereby, the moment of inertia JL of the load can be identified, leading to a better precision for this important parameter used by the control unit to control the orientation of the crane load. The control unit is adapted during operation of the crane by using as a parameter a corrected value of the moment of inertia JL identified during operation of the crane based on the data obtained by measuring the state of the system. Therefore, the control unit does not use a fixed value estimated once and for all, but a value adapted using further information gained during the operation of the crane.
In the method for controlling the rotation of the crane of the present disclosure, the rotational angle φL of the load is advantageously controlled using an adaptive trajectory tracking control. This allows an effective control of the movements of the crane load. For example, a feed forward control can be used to calculate the trajectories of the system variables based on forward integration of the equations of motion of the system and a state feed back control can use data obtained by measuring the state of the system.
In the method for controlling the rotation of a crane load of the present disclosure, advantageously a dynamic model of the system is used to calculate data describing the state of the system, i.e. the trajectories of the system variables. These data can then form the basis for controlling the rotation of the crane load, the dynamic model of the system allowing an accurate description of the system and therefore a precise control of the orientation of the crane load.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, the difference φC between the rotational angle φL of the load and the rotational angle φH of the hook can be varied by the rotator unit. This is advantageously done by using a hydraulic motor for the rotator unit, such that torque can be applied by the rotator unit. This makes it possible to rotate the manipulator and thereby the load about a vertical axis, thereby allowing an orientation of the load in any desired direction.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, torsional oscillations are avoided by an anti-torsional oscillation unit using the data calculated by the dynamic model. This anti-torsional oscillation unit uses the data calculated by the dynamic model to control the rotator unit such that oscillations of the load are avoided. Thereby, the anti-torsional oscillation unit 212 can generate control signals that counteract possible oscillations of the load predicted by the dynamical model. If a hydraulic motor is used for the rotator, the anti-torsional oscillation unit can generate signals for activating the hydraulic motor, thereby applying torque generated by the resulting flow rate.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, the difference φC between the rotational angle φL of the load and the rotational angle φH of the hook is measured by an encoder 414 connected to the rotator unit 318. This encoder makes it possible to exactly measure the difference φC, and thereby helps to control the orientation of the load.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, the movements of a cardanic element guided by the rope are measured to obtain data by which the rotational angle φH of the hook and/or the rotational angle φL of the load can be determined. The cardanic element preferably is connected to the boom head of the crane by a cardanic joint and follows the movements of the rope, on which it is guided by rollers. By measuring the movements of the cardanic element, the movements of the rope can be determined. As the hook is usually suspended on a plurality of ropes, preferably at least two cardanic elements are provided in order to determine the movements of at least two of these ropes. The rotational angle φH of the hook suspended on the ropes and/or the rotational angle φL of the load can then be determined from the data obtained from measuring the movements of the cardanic elements.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, a gyroscope is used to obtain data by which the rotational angle φH of the hook and/or the rotational angle φL of the load can be determined. Using a gyroscope is a particularly effective way of obtaining such data with sufficient precision. The gyroscope can be mounted in different places on the crane. If cardanic elements are used, the gyroscope can be mounted on the cardanic elements to measure their movements, but it is also possible to mount the gyroscope directly on the hook or the manipulator.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, the change {dot over (φ)}H in the rotational angle φH of the hook and/or the changed in the rotational angle φL of the load is measured by a gyroscope. The gyroscope can either be mounted on the hook or the manipulator 20, but preferably on the hook. Gyroscopes can measure the angular velocities {dot over (φ)}H and {dot over (φ)}L, which allows a determination of the rotational angles angle φH of the hook and the φL. If {dot over (φ)}H is measured by the gyroscope, φH can be determined by integration. The rotational angle φL of the load can then be calculated by using the difference φC between the rotational angle φL of the load and the rotational angle φH of the hook measured by the encoder 414. As the value of {dot over (φ)}H measured by the gyroscope will contain noise and an offset, straightforward integration would lead to an accumulation of these errors, leading to poor results in accuracy. Therefore, a disturbance observer 314 is advantageously used to compensate for offset. This allows a more robust estimation of the rotational angle φH from the angular velocity {dot over (φ)}H.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, the dynamical model of the system is based on the equations of motion of a physical model of at least the ropes, the hook and the load. In such a physical model, the hook and the load suspended on the ropes form a torsional pendulum, whose equations of motion can be determined using e.g. the Lagrange formalism. This allows a realistic description of the system and therefore a precise trajectory planning 310 and control.
Advantageously, the moment of inertia JH of the hook and JSp of the manipulator are used as parameters for the control of the rotational angle φL of the load. Even though the moment of inertia JH of the hook and JSp of the manipulator are usually smaller than the moment of inertia JL of the load, they nevertheless contribute to the rotational behaviour of the system and should be accounted for in the calculations and the physical model.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, during the operation of the crane a torque is applied to the load and/or the hook. The data obtained by measuring the state of the system while a torque is applied to the hook and/or the load will allow to estimate the moment of inertia JL of the load, e.g. by using an observer.
Advantageously, the data obtained by measuring the state of the system at least comprises the change {dot over (φ)}H in the rotational angle φH of the hook and/or the changed, in the rotational angle φL of the load in reaction to the torque applied to the load and/or the hook. This data can then be used to estimate the moment of inertia JL of the load, e.g. by comparing data calculated by the dynamic model with the measured data.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, a value of the moment of inertia JL0 estimated on the basis of the mass and the dimensions of the load only is used as an initial value for JL and corrected values JLk are determined in an iterative process in order to identify the moment of inertia JL. This will give a rough estimate of the initial value for JL based on the data that are quickly available, while better estimates are determined during the operation of the crane based on the additional data obtained by measuring the state of the system.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, during operation of the crane data describing the state of the system are calculated by the dynamical model based on a value JL,k−1 of the moment of inertia JL and a corrected value JLk of the moment of inertia JL is determined based on the calculated data and the data obtained by measuring the state of the system in order to identify the moment of inertia JL. This allows a far better estimation of the moment of inertia JL than using the mass and dimensions of the load only.
The moment of inertia JL can advantageously be identified using an observer. This method of estimating the moment of inertia JL uses data calculated by the dynamic model and combines them with data obtained by measuring the state of the system to estimate the parameter JL of the dynamic model. Using an observer for determining variables of the system such as the rotational angle φH of the hook from the angular velocity {dot over (φ)}H measured by the gyroscope had already been known. Here, however, a parameter of the model is determined using an observer, leading to an adaptive control.
As a parameter of the model is estimated by the observer, the problem becomes non-linear, such that advantageously the moment of inertia JL is identified using a non-linear observer. There are different possibilities for implementing a non-linear observer, especially for time-variant models, such as the high-gain approach or the extended Kalman Filter 316.
The last possibility offers a very robust system for quickly estimating parameters of the system, such that advantageously the moment of inertia JL is identified using an extended Kalman Filter.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, a homogeneous distribution of mass inside the load is assumed for the estimation of an initial value JL0 of the moment of inertia JL of the load. This allows a quick calculation that only needs the mass and dimensions of the load as an input.
In a further development of the method for controlling the orientation of a crane load of the present disclosure, noise in the data obtained by measurements is taken into account in the identification of the moment of inertia JL. This will lead to more precision in the estimation of the moment of inertia JL which is based on the measured data and therefore influenced by noise in the measurements.
Advantageously, the noise in the data obtained by measurements is modelled by covariance matrices. This allows a quantitative description of the influence of the noise and can minimize the errors resulting from the noise.
These covariance matrices are advantageously determined experimentally. By testing the control system with different values for the covariance matrices, the best values for a quick and robust estimation of the moment of inertia JL can be determined and used for the observer.
The present disclosure further comprises a system for controlling the orientation of a crane load using any one of the methods described above. Such a control system comprises a control unit for controlling the rotational angle φL of the load. Advantageously, the control unit contains a trajectory planning unit 310 and a trajectory control unit, as well as an observer for estimating the moment of inertia JL.
The present disclosure further comprises a crane, especially a boom crane, comprising a system for controlling the rotation of a crane load using any of the methods described above. Such a crane comprises a hook suspended on ropes, a rotator unit and a manipulator. Advantageously, the crane will also comprise an anti-sway-control system 210 that interacts with the system for controlling the rotation of a crane. If the crane is a boom crane, it comprises a boom that can be pivoted up and down around a horizontal axis and rotated around a vertical axis by a tower. Additionally, the length of the rope can be varied.